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- import numpy as np
- import caffe2.python.models.shufflenet as shufflenet
- import hypothesis.strategies as st
- from hypothesis import given, settings
- import caffe2.python.hypothesis_test_util as hu
- import caffe2.python.models.imagenet_trainer_test_utils as utils
- class ShufflenetMemongerTest(hu.HypothesisTestCase):
- @given(with_shapes=st.booleans(), **hu.gcs_cpu_only)
- @settings(max_examples=2, deadline=None)
- def test_shufflenet_shared_grads(self, with_shapes, gc, dc):
- results = utils.test_shared_grads(
- with_shapes,
- shufflenet.create_shufflenet,
- 'gpu_0/stage1_conv_w',
- 'gpu_0/last_out_L1000'
- )
- self.assertTrue(results[0][0] < results[0][1])
- np.testing.assert_almost_equal(results[1][0], results[1][1])
- np.testing.assert_almost_equal(results[2][0], results[2][1])
- def test_shufflenet_forward_only(self):
- results = utils.test_forward_only(
- shufflenet.create_shufflenet,
- 'gpu_0/last_out_L1000'
- )
- self.assertTrue(results[0][0] < results[0][1])
- self.assertTrue(results[1] < 10 and results[1] > 0)
- np.testing.assert_almost_equal(results[2][0], results[2][1])
- def test_shufflenet_forward_only_fast_simplenet(self):
- '''
- Test C++ memonger that is only for simple nets
- '''
- results = utils.test_forward_only_fast_simplenet(
- shufflenet.create_shufflenet,
- 'gpu_0/last_out_L1000'
- )
- self.assertTrue(results[0][0] < results[0][1])
- self.assertTrue(results[1] < 4 and results[1] > 0)
- np.testing.assert_almost_equal(results[2][0], results[2][1])
- if __name__ == "__main__":
- import unittest
- import random
- random.seed(2006)
- # pyre-fixme[10]: Name `workspace` is used but not defined in the current scope
- workspace.GlobalInit([
- 'caffe2',
- '--caffe2_log_level=0',
- '--caffe2_print_blob_sizes_at_exit=0',
- '--caffe2_gpu_memory_tracking=1'])
- unittest.main()
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